I have been a teaching assistant at Columbia University (2021–2025) and the University of Colorado Boulder (2019–2021), for courses spanning IoT and connected systems, reinforcement learning, blockchain, embedded AI, computer organization, and circuits.
Since 2022 I have mentored undergraduate researchers, including through the NSF REU and Columbia SURE programs. One mentee received a Best Presentation Award; another had their first paper accepted to ACMSE.
Graduate course, Columbia University, Department of Electrical Engineering, 2023
This course covers blockchain fundamentals to advanced topics, including Bitcoin, Ethereum, smart contracts, DeFi, and NFTs. Students will gain a comprehensive understanding of blockchain’s wide-ranging applications and industry impact.
Graduate course, Columbia University, Department of Electrical Engineering, 2022
Reinforcement learning is a powerful tool for learning and sequential decision making, and it is relevant in an enormous range of applications, including robotics, game playing, consumer modeling and healthcare. This class will provide a solid introduction to the field of reinforcement learning and students will learn about the core challenges and approaches, including generalization and exploration. It uses a combination of lectures, and written and coding assignments, to teach key ideas and techniques for RL. The applications in Information systems (video streaming, scheduling, etc) are discussed through lectures and project.
Graduate course, Columbia University, Department of Electrical Engineering, 2022
This course covers blockchain fundamentals to advanced topics, including Bitcoin, Ethereum, smart contracts, DeFi, and NFTs. Students will gain a comprehensive understanding of blockchain’s wide-ranging applications and industry impact.
Graduate course, Columbia University, Department of Electrical Engineering, 2021
This course equips students with key insights into the evolving fields of cyber-physical systems and the Internet of Things (IoT). Covering a broad range of topics, the course features guest lectures from experts and culminates in a hands-on group project where students build a functional IoT system.
Undergraduate course, University of Colorado Boulder, Department of Electrical Engineering, 2021
Studies computer design at the microarchitecture level. Discusses instruction set architecture design, arithmetic and logic unit design, control logic, memory design and caches, simple pipelining, I/O and peripheral devices. Briefly covers aspects of modern computer architecture, such as multicore processors and hardware security.
Undergraduate course, University of Colorado Boulder, Department of Electrical Engineering, 2020
Studies computer design at the microarchitecture level. Discusses instruction set architecture design, arithmetic and logic unit design, control logic, memory design and caches, simple pipelining, I/O and peripheral devices. Briefly covers aspects of modern computer architecture, such as multicore processors and hardware security.
Undergraduate course, University of Colorado Boulder, Department of Electrical Engineering, 2020
Introduces linear circuit analysis and design, including OP-Amps. Presents DC networks, including node and mesh analysis with controlled sources. Analysis of RL and RC circuits for both transient and sinusoidal steady-state responses using phasors. Laplace transform techniques, transfer functions, frequency response, Bode diagrams, resonant circuits, Fourier series expansions, and convolution.
Undergraduate course, University of Colorado Boulder, Department of Electrical Engineering, 2019
Introduces linear circuit analysis and design, including OP-Amps. Presents DC networks, including node and mesh analysis with controlled sources. Analysis of RL and RC circuits for both transient and sinusoidal steady-state responses using phasors. Laplace transform techniques, transfer functions, frequency response, Bode diagrams, resonant circuits, Fourier series expansions, and convolution.